Many different types of data and information are available such as text, articles, lists, and graphics, and many different systems are available for recording and classifying data and information in various structure, such as a common database structure or a spreadsheet, all collectively referred to herein as data and information sources regardless of the type, system, or structure. And many different types of systems have been developed for extracting specific information from various data and information sources, collectively referred to herein as search engines, including Google® search of Google Corporation of Mountain View, Calif., Baidu search of Baidu.com Corporation of Beijing, China, Yahoo!® and AltaVista® searches of Yahoo! Corporation of Sunnyvale, Calif., MSN® and Windows Live® searches of Microsoft Corporation of Redmond, Wash., and like general searching applications; SQL and like customized searching applications; and other information retrieval (IR) systems. And even some systems have been developed for trying to infer and/or calculate information from one or more data and/or information sources, such as identifying trends in data and hypothesis generation, including inference systems, deductive reasoning systems, artificial intelligence systems, neural network systems, semantic network systems, fuzzy logic systems, and other expert systems, collectively referred to herein as inference engines.
Further, some systems allow a user to save preferences and establish preset conditions that can later be used again and/or refined for different purposes, such as a default search strategy that can be refined for various more specific searches area. Some systems are designed for particular types of data and information. And some systems are designed for a particular subject matter domain, and the corresponding operations that might be performed on the data and information available for the particular subject matter domain.
But although techniques have been developed for working with data and information, including many sophisticated search engines and inference engines, it is desirable to improve upon these existing techniques and to provide the further ability for a user to impart his or her knowledge about a domain, including to impart knowledge about a domain separate and apart from a particular search engine or inference engine. While search engines and inference engine provide exceptionally important and useful advantages, these systems, individually and in combination, are principally limited to working with, managing, and creating data and information. For example, there is a need in the art for improved architectures, systems, methods, and computer program products for providing a user with the ability to define and modify an association of data and/or information that is perceived by the user as relevant to a subject matter domain, thereby imparting some of his or her knowledge about the domain, and permitting use of that knowledge to perform discovery process operations on data and information, i.e., to evaluate data and information.